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Deep learning LSTM for predicting thermally induced geometric errors using rotary axes’ powers as input parameters

Huy Vu Ngoc, J.R.R. Mayer, Elie Bitar-Nehme

2022CIRP journal of manufacturing science and technology34 citationsDOI

Topics & Concepts

Artificial intelligenceControl theory (sociology)Computer scienceDeep learningComputer visionEngineeringControl (management)Advanced Measurement and Metrology TechniquesAdvanced machining processes and optimizationAdvanced Numerical Analysis Techniques
Deep learning LSTM for predicting thermally induced geometric errors using rotary axes’ powers as input parameters | Litcius